From: Joi Ito Sent: Tuesday, October 22, 2013 11:26 AM To: Epstein Jeffrey Subject: Fwd: MDF Attachments: signature.asc BTW, getting going with Joscha. He's smart. Let me know if you're =nterested in joining the brain threads. Begin forwarded message: > From: Joscha Bach > Subject: Re: MDF > Date: October 21, 2013 23:56:09 -0400 > To: Joi Ito > Cc: takashi ikegami > Kevin Slavin Greg Borenstein Ari Gesher Martin Nowak > Hi Takashi, hi Ari, hi all, > finally I got around to look at Takashi's talks and his 2010 ACM =rticle. The first thing that came to mind was the distinction between =neat" and "scruffy" AI, which might be described as the clash between =olks that wanted to construct Al by adding function after function, vs. =hose that want to take a massively complex system and constrain it =ntil it only does what it is supposed to do. > The idea of starting from massive data flows is very natural and =heoretically acknowledged, even it is often practically neglected. =ognition, by and large, is an organism's attempt to massively reduce =omplexity, by compressing, encoding, selectively ignoring, abstracting, =redicting. controlling it. Thus, it seems natural to focus on the =echanisms that handle this complexity reduction, which I think is =xactly what most research in computer vision, machine learning, =lassification, robot control etc. is doing. A lot of the work on =roblem solving and learning within cognitive science even works _only_ =n the highest level of abstraction, i.e. grammatical language, regular =oncept structures, ontologies and soon. > If I understand Takashi correctly, he points towards another > =erspective: (please forgive and correct me if I should oversimplify too =uch here) 1. Cognitive systems do not only need to reduce complexity, but also =uild it (for instance, take simple cues or abstract input and use it to =eed a rich, heterogenous, ambiguous and dynamic forest of =epresentations). > 2. Cognitive pro